Title page for etd-0024116-224820


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URN etd-0024116-224820
Author Wei Chang
Author's Email Address No Public.
Statistics This thesis had been viewed 5360 times. Download 28 times.
Department Information Management
Year 2015
Semester 1
Degree Master
Type of Document
Language zh-TW.Big5 Chinese
Title Combining Motion-Sensing Technology with Prediction Strategy to Support English Reading Comprehension
Date of Defense 2016-01-06
Page Count 68
Keyword
  • Kinect
  • Embodied cognition
  • Cognitive Theory of Multimedia Learning
  • Reading strategy
  • Multimodal
  • Abstract Literature in multimodal interaction has not included much research in combing body motion with language learning. This study attempted to base language learning on embodied cognition in multimodal environment. By including multimodal learning with prediction strategy, it is hoped that elementary school students' reading comprehension and reading interest can be enhanced. Ninety-one students of grade 3 to 6 as our participants in National Science and Technology Museum were recruited and assigned to three conditions: Motion condition, Image condition and Text condition. An e-storybook was designed for participants to read and make predictions about the story using the learning modes according to the conditions they are assigned. Motion condition allows for acting out their predictions. Image condition allows for clicking pictures that represents their prediction. Text condition allows for clicking texts without pictures that represent their prediction. Pre- and post-test results showed that overall there is no significant difference between the three conditions. However, further analysis showed that when participants were divided into high group and low group based on their pre-test reading scores, high group in the Motion condition scored significantly lower than the other conditions on the reading comprehension. No significant difference was found for the low group among the three conditions. This finding suggests that body motions can interfere with reading comprehension when high-level participants used body motion to make prediction. However, in terms of reading interest, questionnaire results showed that Motion condition significantly led to higher ratings on reading interest than the other two conditions. Overall, it is suggested that images, motions and texts have similar effect on story comprehension when they are combined with prediction strategy in the multimodal interactive environment. It is recommended that images and motions can be combined with prediction strategy to increase reading interest and adaptive learning mechanism can be designed to address individual differences when motions are integrated into story reading.
    Advisory Committee
  • Pei-Chen Sun - chair
  • Jun-Ming Su - co-chair
  • Hong-Ren Chen - co-chair
  • Wu-Yuan Huang - co-chair
  • Nian-Shing Chen - advisor
  • Files
  • etd-0024116-224820.pdf
  • Indicate in-campus at 5 year and off-campus access at 99 year.
    Date of Submission 2016-01-27

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